Summary In today's episode, I investigate the root causes of AI hallucinations and provide a systematic debugging process to fix them. Here's what this means for you. You can ensure your AI reports remain accurate and reliable by following a structured troubleshooting workflow. You'll also learn these concepts: the four main triggers of hallucinations, how…
Summary In today's episode, I explain why plain text serves as the gold standard for interacting with generative AI models. Here's what this means for you. You will achieve more accurate results and minimize errors by simplifying the data you provide to AI. You'll also learn these concepts: why plain text outperforms complex file formats,…
Summary In today's episode, I explain the causes of AI hallucinations and how you can prevent them in your data processes. Here's what this means for you. You gain the ability to verify and improve the reliability of AI-generated information. You'll also learn these concepts: how probability differs from truth, why models prioritize helpfulness over…
“Every lie incurs a debt to the truth. Sooner or later, that debt is paid.” – Valery Legasov Warning: politics ahead! Changing data does not change reality. For analytics professionals, analytics is all about explaining what happened. That’s literally the purpose of analytics, so we can understand what happened and then make decisions about how…
There’s been a lot of confusion about what the new OpenAI gpt-oss models are and what they’re good for. So let’s clear the air a bit. First and foremost, it is NOT a drop-in ChatGPT replacement. It is far too small and has far too little knowledge to be a good all purpose general foundation…
For my sustainability-minded friends, Google has some new data. Gemini has some very cool, very good efficiency numbers in terms of environmental impact. Here’s how much a single prompt costs the environment in Google Gemini: 0.24 watt-hours, equal to 9 seconds of watching TV. 0.03 grams of CO2, equal to 2 breathes you take 0.26…
Summary In today's episode, I walk through a practical workflow for extracting insights from qualitative data using generative AI, from scraping Reddit forums to validating course pricing against ideal customer profiles. Here's what this means for you. You gain a repeatable method for turning messy, unstructured customer feedback into actionable strategy grounded in real conversations…
There is no life in AI. Let’s be absolutely clear that people who believe AI to be conscious, to be sentient, to be alive… no. There is no life here. Generative AI is predominantly token prediction. When you use these tools and you look under the hood at what’s going on, when you go behind…
